{"id":26634,"date":"2026-01-20T20:39:36","date_gmt":"2026-01-21T01:39:36","guid":{"rendered":"https:\/\/blog.utc.edu\/campus-weekly\/?p=26634"},"modified":"2026-02-02T16:40:24","modified_gmt":"2026-02-02T21:40:24","slug":"notice-of-final-defense-amin-amiri-to-present-doctoral-research","status":"publish","type":"post","link":"https:\/\/blog.utc.edu\/campus-weekly\/2026\/01\/notice-of-final-defense-amin-amiri-to-present-doctoral-research\/","title":{"rendered":"Notice of Final Defense &#8211; Amin Amiri to Present Doctoral Research"},"content":{"rendered":"\n<p>The UTC Graduate School is pleased to announce that\u00a0Amin Amiri will present Doctoral research titled,\u00a0Personalized and Adaptive Therapeutic Music Generation from Biosignals Using Knowledge-Guided Multimodal Large Language Models on\u00a002\/09\/2026 at\u00a010 AM via Zoom: <a href=\"https:\/\/tennessee.zoom.us\/j\/85062104916\"><strong>https:\/\/tennessee.zoom.us\/j\/85062104916<\/strong><\/a> (password 708225). Everyone is invited to attend.\u00a0<br><br>Computer Science<br><br>Chair:\u00a0Dr. Yu Liang<br><br>Co-Chair:\u00a0Dr. Dalei Wu<br><br>Abstract:<br><br>AI-enabled music therapy has the potential to expand access to individualized, non-pharmacologic interventions, but clinically viable therapeutic generation requires more than high-fidelity synthesis: systems must (i) personalize content to a patient\u2019s physiological and contextual state, (ii) remain stable over long horizons, and (iii) satisfy safety- and protocol-driven constraints. This dissertation introduces Qmusic-MLLM, a knowledge-guided multimodal framework that operates in discrete token spaces to enable scalable, controllable, and extensible therapeutic generation across heterogeneous modalities. Methodologically, therapeutic personalization is driven by a large-language-model (LLM) controller that discloses individualized therapeutic modalities (such as relaxation, cognitive engagement, or affect regulation) from multimodal biometric context and translates those needs into auditable constraints and long-horizon plans. To support real-time, high-fidelity multimodal fusion, a universal tokenization interface, the Harmonizer ecosystem, converts continuous signals into transformer-compatible discrete tokens. Empirically, the base Harmonizer demonstrates state-of-the-art reconstruction quality versus modern neural codecs or tokenizers across speech and music benchmarks, indicating a strong foundation for reliable downstream control. Building on the token interface, EEG-Harmonizer compresses multichannel EEG into compact neural tokens and, together with an Electrode-Aware Importance classifier, enables robust cross-subject cognitive or affective state discrimination for neuro-conditioned generation. For future immersive extensions, Video-Harmonizer provides high-resolution video tokenization (4K\/8K, 30\/60 fps) and shows substantial improvements over recent video tokenizers, including Microsoft VidTok and NVIDIA Cosmos tokenizer baselines, while significantly reducing training cost under limited GPU resources. To incorporate therapeutic domain knowledge and reduce unsupported content, evidence-grounded reasoning is integrated using Chain-of-Thought planning and Retrieval-Augmented Chain-of-Thought (RAG-CoT). In RAG-CoT, curated external corpora are indexed and retrieved to supply non-parametric knowledge that conditions plan generation and document-conditioned responses (demonstrated with medical references, including Schwartz\u2019s Principles of Surgery and Kaplan &amp; Sadock\u2019s Synopsis of Psychiatry). The overall architecture is designed to remain backend-agnostic across LLM families. Closed-loop adaptation is formulated as an EEG-grounded contextual bandit that optimizes a prompt-selection policy using immediate alignment- and safety-weighted rewards. Finally, Biomedical-Harmonizer extends the tokenization ecosystem to cardiac electrophysiology by converting multi-lead ECG into high-fidelity discrete token streams for multimodal patient-state modeling. Across these components, a subject-disjoint validation protocol is emphasized to assess generalization without subject-specific leakage. Together, the proposed framework establishes a scalable foundation for personalized, knowledge-grounded, and physiologically adaptive therapeutic music generation, with clear paths toward graph-based retrieval, richer multimodal conditioning, and prospective clinical evaluation.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The UTC Graduate School is pleased to announce that\u00a0Amin Amiri will present Doctoral research titled,\u00a0Personalized and Adaptive Therapeutic Music Generation from Biosignals Using Knowledge-Guided Multimodal Large Language Models on\u00a002\/09\/2026 at\u00a010 AM via Zoom: https:\/\/tennessee.zoom.us\/j\/85062104916 (password 708225). Everyone is invited to attend.\u00a0 Computer Science Chair:\u00a0Dr. Yu Liang Co-Chair:\u00a0Dr. Dalei Wu Abstract: AI-enabled music therapy has the&hellip; <\/p>\n<p class=\"more-link-wrap\"><span><a class=\"more-link button text\" href=\"https:\/\/blog.utc.edu\/campus-weekly\/2026\/01\/notice-of-final-defense-amin-amiri-to-present-doctoral-research\/\"><span>Continue Reading <\/span><\/a><\/span><\/p>\n","protected":false},"author":1493,"featured_media":24306,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[8,15,120183,120186],"tags":[],"class_list":{"0":"post-26634","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-campus","8":"category-faculty-staff","9":"category-news","10":"category-students-news","11":"entry"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Notice of Final Defense - Amin Amiri to Present Doctoral Research - Campus Updates<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/blog.utc.edu\/campus-weekly\/2026\/01\/notice-of-final-defense-amin-amiri-to-present-doctoral-research\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Notice of Final Defense - Amin Amiri to Present Doctoral Research - Campus Updates\" \/>\n<meta property=\"og:description\" content=\"The UTC Graduate School is pleased to announce that\u00a0Amin Amiri will present Doctoral research titled,\u00a0Personalized and Adaptive Therapeutic Music Generation from Biosignals Using Knowledge-Guided Multimodal Large Language Models on\u00a002\/09\/2026 at\u00a010 AM via Zoom: https:\/\/tennessee.zoom.us\/j\/85062104916 (password 708225). Everyone is invited to attend.\u00a0 Computer Science Chair:\u00a0Dr. Yu Liang Co-Chair:\u00a0Dr. Dalei Wu Abstract: AI-enabled music therapy has the&hellip; Continue Reading\" \/>\n<meta property=\"og:url\" content=\"https:\/\/blog.utc.edu\/campus-weekly\/2026\/01\/notice-of-final-defense-amin-amiri-to-present-doctoral-research\/\" \/>\n<meta property=\"og:site_name\" content=\"Campus Updates\" \/>\n<meta property=\"article:published_time\" content=\"2026-01-21T01:39:36+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-02-02T21:40:24+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/blog.utc.edu\/app\/uploads\/sites\/138\/2025\/09\/Campus-20-230.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"600\" \/>\n\t<meta property=\"og:image:height\" content=\"381\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Chuck Wasserstrom\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Chuck Wasserstrom\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/blog.utc.edu\\\/campus-weekly\\\/2026\\\/01\\\/notice-of-final-defense-amin-amiri-to-present-doctoral-research\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/blog.utc.edu\\\/campus-weekly\\\/2026\\\/01\\\/notice-of-final-defense-amin-amiri-to-present-doctoral-research\\\/\"},\"author\":{\"name\":\"Chuck Wasserstrom\",\"@id\":\"https:\\\/\\\/blog.utc.edu\\\/campus-weekly\\\/#\\\/schema\\\/person\\\/028a71bd6215de86078a717b45430622\"},\"headline\":\"Notice of Final Defense &#8211; 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